Digital Transformation, Startup-Style, with Self-Service Data

I bet when you think about digital transformation, it conjures a large established enterprise transforming itself. But guess what, startups also do, and must, constantly transform themselves! The willingness to pivot and reinvent is core to a successful startup’s growth and maturity.

You know what else startups have in common with large enterprises? They can amass vast amounts of data, and very quickly. Unleashing this data is key to truly understanding and growing the business in a highly dynamic and competitive marketplace. But how might a startup do that?

Adaptive Biotechnologies tells a very interesting story of their own startup-style data-driven digital transformation. Adaptive Biotechnologies is a thriving biotech startup, that has grown in leaps and bounds, organically and through acquisitions. They were accumulating a lot of data coming in from multiple sources and systems. Several analysts were already using Tableau, in combination with spreadsheets, for data analysis.

However, Adaptive Biotechnologies did not have a data warehouse or a disciplined data management approach yet. They realized that they needed to become truly data-centric to understand and successfully evolve and grow their business. To that end, they needed to build a robust analytics and data management solution. This would empower their Tableau users to conduct and consume analysis based on trusted, consistent and relevant data. But, they absolutely needed their new self-service analytics environment to fully support business agility, fueled by timely and accessible data.

If you are wondering how you can become both disciplined and agile at the same time, here are some of the key solution elements that enabled Adaptive Biotechnologies’ agile analytics solution:

Cloud Self-Service Analytics: Adaptive Biotechnologies opted for an architecture that included public cloud storage of data for analytics and Informatica’s iPaaS (Integration Platform as a Service) for cloud data integration, all delivering trusted, timely and relevant data for analysis and visualization by their Tableau users. This enables scalability and agility of their analytics environment. They have the flexibility to readily grow their environment as data volumes increase, rapidly change data models and accommodate changing business processes and quickly onboard new data sources. It also allows them to easily administer and manage their data management system and keep costs low.

Ad Hoc Analytics & Operational Reporting: As analysts are fond of saying, we often don’t know what we don’t know. That’s where experimentation comes in. But once we find an analysis we like, it’s good to operationalize and automate it, so all can share the goodness. Adaptive Biotechnologies opted to combine a cloud data warehouse with a cloud data lake in their architecture. The cloud data lake stores vast amounts of raw data, mass-ingested by iPaaS from multiple sources, to facilitate ad hoc analysis and experimentation by Tableau analysts. The cloud data warehouse hosts all the standardized and normalized data, integrated by iPaaS, from multiple sources, for operationalized reporting and analysis in Tableau.

Automatic integration of multiple systems in data ecosystem: Adaptive Biotechnologies had very siloed views of data, created within multiple SaaS and legacy systems, including Salesforce, NetSuite, business-specific systems such as bioinformatics and samples management, flat files, customer portal and marketing systems. Additionally, B2B data was coming in from outside partners such as payment processors and other suppliers. Manually integrating this siloed data was a time-consuming task, that could easily take hours each day, before analysis or business processes could commence. Additionally, they often needed to rapidly add new systems to their ecosystem and retire others. Adaptive Biotechnologies decided to implement an automated, repeatable, cloud-based approach to data integration, using Informatica’s iPaaS solution. This allowed them to intuitively and quickly integrate data from multiple sources, using prebuilt connectors and templates, easily onboard new systems, seamlessly scale data integrations and eliminate time-consuming administration tasks. Data can now be automatically integrated into their cloud data lake, cloud data warehouse or directly into their Tableau environment.

Business & IT Collaboration: One of the important contributors to Adaptive Biotechnologies’ agile analytics is the ability for the business users and IT team to closely collaborate and iterate. IT empowers Tableau business users with ad hoc analytics, of IT-certified data, integrated from multiple sources, in the cloud data lake. Those analysts and business “super users” explore the raw data in the lake and prototype and build reports. Based on ad hoc analysis, the teams work together to determine which data and reports should be persisted and operationalized and what business logic should be implemented in the data warehouse. This fosters a culture of rapid experimentation and discovery, reuse and sharing of proven analysis and constant improvement to the process. The team shares that they see the act of creating Business Intelligence (BI) as fostering a collaborative discussion on business practices and unifying processes and definitions. They feel that their new agile BI stack facilitates that exploration.

Infuse an analytical culture throughout: Truly becoming data-centric is a powerful transformation. For a startup it can be critical to thriving and even surviving. Like every transformation, it’s more of a journey than an overnight endeavor. And like every transformation, it requires more than new systems and processes. It also calls for a cultural change. At Adaptive Biotechnologies, the IT team has lead this journey of implementing a disciplined analytics-focused culture. Once the business teams realized the vast potential brought on by this approach, the analytics-focus really took off and became strongly embedded in the company culture. Fast-forward a few years later, the analytics and data management solution in place, facilitates the discussion of actually understanding the business!